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The demonstration in this video will show you the effect of proportional, derivative, and integral control on a real system. It's a DC motor connected to an optical rotary encoder (quadrature) and is controlled by a digital control loop implemented on a TI Launch Pad MSP432. It uses a seriThe demonstration in this video will show you the effect of proportional, derivative, and integral control on a real system. It's a DC motor connected to an optical rotary encoder (quadrature) and is controlled by a digital control loop implemented on a TI Launch Pad MSP432. It uses a series of timers and interrupts to generate the PWM signals to the H-Bridge motor driver, read the pulses from the encoder, and calculate the control effort using a PID control algorithm. It also implements an anti-windup algorithm to improve the system stability since this is a real system and the motor saturates easily.
If you listen, you can hear the PWM signal whine as it adjust the current to the motor. When I push on the flag with my hand you will hear it go quiet. That's when the PWM is at 100% duty cycle and the audible PWM AC current going to the motor is now DC.
Post a comment if you liked the video!
You can download the code, design files, and parts list here:
https://github.com/arduinoNube/digita...
(out of date: https://sourceforge.net/projects/digi... )
Enjoy!
http://www.gregoryholst.com…...more
The demonstration in this video will show you the effect of proportional, derivative, and integral control on a real system. It's a DC motor connected to an optical rotary encoder (quadrature) and is controlled by a digital control loop implemented on a TI Launch Pad MSP432. It uses a series of timers and interrupts to generate the PWM signals to the H-Bridge motor driver, read the pulses from the encoder, and calculate the control effort using a PID control algorithm. It also implements an anti-windup algorithm to improve the system stability since this is a real system and the motor saturates easily.
If you listen, you can hear the PWM signal whine as it adjust the current to the motor. When I push on the flag with my hand you will hear it go quiet. That's when the PWM is at 100% duty cycle and the audible PWM AC current going to the motor is now DC.
Post a comment if you liked the video!
You can download the code, design files, and parts list here:
https://github.com/arduinoNube/digita...
(out of date: https://sourceforge.net/projects/digi... )
Enjoy!
http://www.gregoryholst.com
The demonstration in this video will show you the effect of proportional, derivative, and integral control on a real system. It's a DC motor connected to an optical rotary encoder (quadrature) and is controlled by a digital control loop implemented on a TI Launch Pad MSP432. It uses a series of timers and interrupts to generate the PWM signals to the H-Bridge motor driver, read the pulses from the encoder, and calculate the control effort using a PID control algorithm. It also implements an anti-windup algorithm to improve the system stability since this is a real system and the motor saturates easily.
If you listen, you can hear the PWM signal whine as it adjust the current to the motor. When I push on the flag with my hand you will hear it go quiet. That's when the PWM is at 100% duty cycle and the audible PWM AC current going to the motor is now DC.
Post a comment if you liked the video!
You can download the code, design files, and parts list here:
https://github.com/arduinoNube/digita...
(out of date: https://sourceforge.net/projects/digi... )
Enjoy!
http://www.gregoryholst.com
tuning the integral value | tune the proportional entering the integral | change the ramp rate at the set point | start with a proportional | reached the setpoint | set the derivative back to zero | start playing and tuning to different scenarios
calculates the corrections for the four motors | calculates the current difference between the gyro and the receiver | bringing the output of the ai controller back to zero | implement the pid controller into the arduino code | turn on the led | set a roll setpoint to zero | dividing the receiver signals by three | set up the pid settings of this particular multicopter
Introduction | Sample flight with final PID tune | Make sure your quad is mechanically sound | Test flight to set up filters | Blackbox analysis of first test flight | Recommended filter settings based on first test flight | Discussion: Find your Max D Gain | Set pidsum_limit and pidsum_limit_yaw | Test flight with Master Multiplier at 1.5 | Test flight with Master Multiplier at 1.4
Oscillates a little and overshoots quite a bit | Ok! The oscillations are gone and the steady state error is ok | Now, how do we get rid of the rest of the steady state error? | Integral Control! | You should be able to see the controller bring the arm back to the exact same position every time | The key here is that this is a REAL system and not an ideal one. To fix this, we need anti-windup code.
Introduction | How quadcopters and PIDs work | Settings to change in Betaflight | High and low PID value examples | Tuning demonstration and explanation | Conclusion